Abstract
ObjectivesOur aim was to estimate the rate of data linkage error in Hospital Episode Statistics (HES) by testing the HESID pseudoanonymisation algorithm against a reference standard, in a national registry of paediatric intensive care records.SettingThe Paediatric Intensive Care Audit Network (PICANet) database, covering 33 paediatric intensive care units in England, Scotland and Wales.ParticipantsData from infants and young people aged 0–19 years admitted between 1 January 2004 and 21 February 2014.Primary and secondary outcome measuresPICANet admission records were classified as matches (records belonging to the same patient who had been readmitted) or non-matches (records belonging to different patients) after applying the HESID algorithm to PICANet records. False-match and missed-match rates were calculated by comparing results of the HESID algorithm with the reference standard PICANet ID. The effect of linkage errors on readmission rate was evaluated.ResultsOf 166 406 admissions, 88 596 were true matches (where the same patient had been readmitted). The HESID pseudonymisation algorithm produced few false matches (n=176/77 810; 0.2%) but a larger proportion of missed matches (n=3609/88 596; 4.1%). The true readmission rate was underestimated by 3.8% due to linkage errors. Patients who were younger, male, from Asian/Black/Other ethnic groups (vs White) were more likely to experience a false match. Missed matches were more common for younger patients, for Asian/Black/Other ethnic groups (vs White) and for patients whose records had missing data.ConclusionsThe deterministic algorithm used to link all episodes of hospital care for the same patient in England has a high missed match rate which underestimates the true readmission rate and will produce biased analyses. To reduce linkage error, pseudoanonymisation algorithms need to be validated against good quality reference standards. Pseudonymisation of data ‘at source’ does not itself address errors in patient identifiers and the impact these errors have on data linkage.
Highlights
To allow analysis of patients use of healthcare across hospitals and over time, a data resource needs to link together episodes of hospital care that belong to the same person.[1]
Each record is submitted to the Health and Social Care Information Centre (HSCIC), who use the HESID pseudonymisation algorithm[2] to identify all hospital records that should be linked together across the National Health Service (NHS) in England, using a range of patient identifiers commonly used internationally in administrative data.[2]
Reference standard: PICANet Patient Identification Number The hospital data were drawn from the Paediatric Intensive Care Audit Network (PICANet) database for 33 paediatric intensive care units in England, Scotland and Wales (1 January 2004 to 21 February 2014)
Summary
To allow analysis of patients use of healthcare across hospitals and over time, a data resource needs to link together episodes of hospital care that belong to the same person.[1] In England, Hospital Episode Statistics (HES) are a data set containing data on admissions, outpatient appointments and Accident and Emergency attendances at National Health Service (NHS) hospitals in England.[1] Each record is submitted to the Health and Social Care Information Centre (HSCIC), who use the HESID pseudonymisation algorithm[2] to identify all hospital records that should be linked together across the NHS in England, using a range of patient identifiers commonly used internationally in administrative data (eg, date of birth, sex, postcode, ID number).[2] HES are released to researchers, with patient identifiers removed. These data are used widely and yet the extent of data linkage error in HES has undergone no investigation against an external reference standard
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